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Machine Minds, Perfect Smiles: The Future of AI in Orthodontics: A Contemporary Review

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Artificial Intelligence (AI) is rapidly transforming orthodontics, evolving from a supplementary aid to a potential cornerstone of modern dental practice. By leveraging the capabilities of machine learning (ML), deep learning (DL), and artificial neural networks (ANNs), orthodontists can now process and interpret massive multimodal datasets with unprecedented precision and efficiency.1,2,4,15These datasets range from traditional cephalometric radiographs to complex three-dimensional imaging modalities such as cone-beam computed tomography (CBCT) and intraoral scans.3 Recent advancements have demonstrated that AI-powered diagnostic tools can equal, and in some cases surpass, the accuracy of seasoned clinicians in specific tasks such as cephalometric landmark identification or growth prediction.5 Beyond diagnostics, AI offers powerful applications in treatment planning, biomechanical tooth movement simulations, surgical planning, patient compliance monitoring, and even the customization of orthodontic appliances through integration with 3D printing technologies.12,13,14 This expanded review aims to provide an in-depth exploration of AI’s principles, current clinical applications, limitations, and future directions in orthodontics. The discussion draws upon literature from 2019 to 2025, case examples, and real-world clinical adoption scenarios. Ethical, legal, and technical considerations—such as patient data privacy, algorithmic bias, regulatory compliance, and seamless integration into clinical workflows—are analyzed in detail.16,17,18,19 Ultimately, we envision a future in which AI-enhanced orthodontics merges data-driven decision-making with the artistry of clinical expertise, resulting in care that is individualized, efficient, and firmly evidence-based.
Title: Machine Minds, Perfect Smiles: The Future of AI in Orthodontics: A Contemporary Review
Description:
Artificial Intelligence (AI) is rapidly transforming orthodontics, evolving from a supplementary aid to a potential cornerstone of modern dental practice.
By leveraging the capabilities of machine learning (ML), deep learning (DL), and artificial neural networks (ANNs), orthodontists can now process and interpret massive multimodal datasets with unprecedented precision and efficiency.
1,2,4,15These datasets range from traditional cephalometric radiographs to complex three-dimensional imaging modalities such as cone-beam computed tomography (CBCT) and intraoral scans.
3 Recent advancements have demonstrated that AI-powered diagnostic tools can equal, and in some cases surpass, the accuracy of seasoned clinicians in specific tasks such as cephalometric landmark identification or growth prediction.
5 Beyond diagnostics, AI offers powerful applications in treatment planning, biomechanical tooth movement simulations, surgical planning, patient compliance monitoring, and even the customization of orthodontic appliances through integration with 3D printing technologies.
12,13,14 This expanded review aims to provide an in-depth exploration of AI’s principles, current clinical applications, limitations, and future directions in orthodontics.
The discussion draws upon literature from 2019 to 2025, case examples, and real-world clinical adoption scenarios.
Ethical, legal, and technical considerations—such as patient data privacy, algorithmic bias, regulatory compliance, and seamless integration into clinical workflows—are analyzed in detail.
16,17,18,19 Ultimately, we envision a future in which AI-enhanced orthodontics merges data-driven decision-making with the artistry of clinical expertise, resulting in care that is individualized, efficient, and firmly evidence-based.

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